Time series are data observed over time (either in continuous time or at discrete time periods).

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Reverse engineer a predictive model from a time series graph

I have found some real estate plots in a scientific article. These graphs mainly describe, the believes of the author of the development of the real estate market in the future for certain countries. ...
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65 views

Outlier Detection in Time-Series: How to reduce false positives?

I'm trying to automate outlier detection in time-series and I used a modification of the solution proposed by Rob Hyndman here. Say, I measure daily visits to a website from various countries. For ...
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20 views

How to merge overlapping discontinued data time series?

I have two datasets consisting of the US Federal debt held by Federal banks with a timespan covering the period 1953Q1 to 1988Q4 and 1970Q1 to 2014Q2. (series FDHBFRB and FDHBFRBN from the FRED ...
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46 views

STL-decomposition of a time series with deterministic trend and seasonality

what is the relationship between STL-decomposition and deterministic components of time series like trend or seasonality? I have a time series with deterministic trend and deterministic seasonality, ...
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21 views

Unit root in shares

Suppose that dependent variable is a share of sth (for example it is a % of positive answers to the same question in each period of time t). If data shows the unit ...
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3answers
134 views

How do I detrend time series?

How do I detrend time series? Is it ok to just take first difference and run a Dickey Fuller test, and if it is stationary we are good? I also found online that I can detrend the time series by ...
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23 views

Matching two power signals for similarity

Below are the images of two signals that i plotted. Both the signals are from fridge belonging to different houses. Visually looking at the plot i can tell that these plots belong to fridge as they ...
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25 views

Longitudinal data: baseline effect versus random intercept 2

My question follows this post: Longitudinal data: baseline effect versus random intercept The topic is very interesting and I have two further questions, one very practical and another about ...
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22 views

Cross correlation of two power signals

I have two devices and their power usage data. I am trying to see how co related these two devices are. i.e If i use device 1 then how often i am using device 2. It will be helpful if anyone can ...
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35 views

PCA on spatial precipitation data time series

I have precipitation time series data stored in a 3D matrix called 'pre' (dim1/2=position (index), dim3=time). I want to do a principal component analysis in order to detect the main variance and thus ...
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12 views

Extract ocasional peak and recent trend from noisy time series with threshold driven sampling of an impulse signal

I have event sampled time data for several measurements for a large number of units. The data is recorded only when the measurement is above a threshold. The measurement amplitude increases, and then ...
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96 views

ARIMAX with a specified nonlinear model using the arima function in R

I am interested in fitting an ARIMAX model using R. As known, ARIMAX can be understood as a composition of ARIMA models and regression models with exogenous (independent) variables. I have a time ...
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26 views

How to improve linear model generalization when autocorrelation is present?

I have features $X_t$ and response $Y_t$ (all continuous variables) and my objective is to find the best estimate of $f(X_t)=Y_t$ where $f$ is linear, and 'best' is defined as lowest generalisation ...
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106 views

What's the minimum sample size required to do a time series analysis?

I'd like to know the minimum number of monthly data points required to do time series analysis with the seasonality effect in forecasting. I read some articles & they were saying that 50 or 60 ...
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1answer
186 views

Predicting Y from a regression model for dY

I have some time series data where I'm modelling temperature as a function of various predictors. On physical grounds, I can expect that $$\frac{dT}{dt} \propto T_a - T$$ where $T_a$ is the ambient ...
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59 views

Time series with autoregressive error

How can I in R fit a time series, $x_t$, with external regressors, $v_t$, and an autoregressive error? This time series model is given as follows, $x_t = \beta v_t + \epsilon_t$ where $\epsilon_t = ...
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70 views

Multivariate Time Series Forecasting in R - data in 10 minute intervals

I have data where an observation was made in 10 minute intervals for 8 weeks. I have around 170 variables that were measured every 10 minutes. I am trying to use multivariate time series analysis to ...
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36 views

What does a linear/geometric probability in time series mean?

In some discrete time series I analyzed I'd like to interpret whether there is a meaning to the observed probability model. The data is some discrete time series with a population of objects which at ...
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1answer
106 views

stationarity in time series

I'm learning a Time series course and I have a few questions. Strictly stationary is a process if the joint distribution of $X_{t1},X_{t2},...,X_{tm}$is the same as the joint distribution of ...
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7 views

How to fit a series into another one so that their mutual information is minimized?

I am building a multivariate model of an output series. I have many series-candidates for inputs. I want to select the inputs based on the mutual information between these inputs and the output. My ...
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21 views

Glue time series back together

I have a long time series whose distribution I don't know. I take snapshot of a fix window at random places of the time series to get a set of equal length shorter time series. Now without the help of ...
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25 views

Do we fit this time series data with time series model or spline?

Basically, I have the following data with the number of item A on the vertical axis and the time on the horizontal axis (from 1st hour to the 24th hour). I don't have much experience in fitting a ...
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28 views

Time series and ACD model

When we say fractional gaussian noise is subordinated to Autoregressive Conditional Duration model, what does it mean (explanation using equation will be great)?
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39 views

Analysis of irregularly sampled time series

What is the difference between irregularly sampled time series and non-linear time series? Also, what are the best methods for the analysis of irregularly sampled time series? Are there any sample ...
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1answer
53 views

How to build a function with the result of auto.arima in R?

I use: fit = auto.arima(Y, xreg=X) in R to get ARIMA(1,0,0), result as follows: ...
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65 views

Counterintuitive result when comparing two groups of time series

I have two groups of time series and I am testing the hypothesis that the groups can be distinguished in some way. Each time series is measurements of an individual’s pupil size as they listen to an ...
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1answer
60 views

Understanding $O_p$

One thing I feel like I have never mastered is the concept of $O_p$ convergence and how to use it. I understand the basic idea and what bounded in probability means, but I always have a hard time ...
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51 views

Filtering of time series

I would like information (references) about the reason why time series should be filtered before being used in a VAR model. Thank you in advance, Nikos.
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41 views

Autocovariance of an AR(3) process

I am given a general equation of an AR(3) process : $Y_t\:=\:e_t\:+\:\Phi _1\:Y_{t-1}+\:\Phi _2Y_{t-2}\:\:+\:\Phi _3Y_{t-3}$ I want to find the $\gamma _0$ of the AR(3) process but I am not too sure ...
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17 views

cointegration analysis for different level stationary series

I have a data set of of three variables: imports, exports and GDP. The import variable is I(1), but the export variable is I(1) only for constant and constant and trend but not for none. Similarly, ...
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49 views

what is 1-step ahead prediction for this AR(2) model?

AR(2) model : rt= 1.2rt-1 - 0.35 rt-2 +at, Var(at)=16 Suppose that r300 = 7, r299=5, and r298=6 What is the 1-step ahead prediction of r301 at the forecast origin T=300? Compute the variance of ...
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34 views

How much training data is enough for seasonal time series forecast

I am new to times series forecast. If I have data(single variable and timestamp) with double seasonality periods, which are 288 and 1056. And I use tbats in R to build time series data and then ...
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32 views

HMM: class residience time from time series

I'm a newbie of the statistica subject. I've seen that HMM could be used in order to model state and state transitions for time series and, since I only know that in Markov Models I could state the ...
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53 views

Using 2 sample T test in time series data

I have two data series (not stationary) and I would like to see if the mean of series 1 is significantly different when a certain condition (on the other series) is met. The theory is that when ...
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41 views

Can I remove seasonality from a cross-correlation using LOESS?

I’m attempting to determine if relationships between two abiotic variables: river discharge (flow; $m^3/s^{-1}$) , temperature ($^oC$) and a response: juvenile fish biomass ($g/m^2$) have any ...
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117 views

Probability distribution of binary time series

I am unable to understand concepts related to the probability distribution of binary time series. This is from the book Binary time series by Benjamin Kedem, vol 52 Let $X_t$, t =0,1,... be a binary ...
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61 views

how to use arima to do mean model

I am learning arima by this site: http://people.duke.edu/~rnau/411home.htm and I want to get the same result as following notes: ...
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19 views

Maximum Lag Length in Granger Causality Test for intraday ,1 minute, time series?

I have 2 time series having 1950 observations each. The time series represent intraday, 1 minute, close prices of stocks. Those 1950 observations cover period of 5 trading days, meaning that each ...
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23 views

prediction of variable in the future?

I have some data from sensors in my phone.I have their respective battery levels at each timestamp the sensor readings were recorded in phone.My aim is to be able to predict, lets say that i have ...
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73 views

Why are econometric analyses valid when the subject of study is inherently different?

I am reading numerous articles pertaining to unemployment as references for my own work. Yet I've encountered many where they use long time series in countries which have had some sort of pertinent ...
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47 views

Seeking basic advice re. contingency matrix for time-limited predictions

I am looking for advice on how to construct a contingency matrix ... A subject is measured on day 1 and a score is computed. This is repeated daily generating a series of scores. If on a given day ...
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34 views

Vector autoregression with interval lag terms in R?

I'd like to perform vector autoregression on a two variable system. I know that the signals $x$ and $y$ have a time lag of > 100 time points, and thus any fit with that many time lag parameters is ...
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79 views

Simple Time Series Analysis

Suppose we have collected a set of data points $\{a_{t}\}$ at time $t = 1, 2, ..., t', ..., n$. Each data point consists of the following attributes: ...
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33 views

Testing Contemporaneous Correlation

Suppose I have the following time series: ...
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35 views

How can I make sure that an LDA implementation works?

I am currently experimenting with neural nets for classification of on-line handwritten data (hence: not pixels, but time series data). To do so, I use several toolkits (internal development of my ...
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231 views

very high frequency time series analysis (seconds) and Forecasting (Python/R)

I have high frequency data (observations separated by seconds), which I'd like to analyse and eventually forecast short-term periods (1/5/10/15/60 min ahead) using ARIMA models. My whole data set is ...
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1answer
25 views

relationships between 3 variables

I have 3 data sets. one is the water level of a lake at 15min intervals, one is the water level of a pond next to the lake (also at 15min intervals) and one is the wind speed over both the lake and ...
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38 views

Identifiability in linear regression and time series

The multivariate linear regression model is given by $\mathbf{y} = \mathbf{X}\boldsymbol{\beta} + \boldsymbol{\epsilon}$, where $\boldsymbol{\epsilon} \sim \mathcal{N}(\mathbf{0, ...
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How to determine the correlation between data sets with the same period but different sample rates?

I am trying to determine the correlation between two sets of data points which span the same time period (20 minutes) but have different resolutions. The first set was recorded at 1-minute intervals, ...
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26 views

How to validate a lognormal random walk for time series data

I am currently working on a project where I need to simulate the prices of a set of $D$ substitutable commodities over time. I was hoping to do this using the following $D$-dimensional lognormal ...